Face space is a powerful framework used to explain various face processing phenomena in humans, including poor recognition memory for unfamiliar faces and other-race effects, but it has yet to be applied to other species. We examined whether chimpanzee (Pan troglodytes) face processing would conform to a face space framework. Five chimpanzees discriminated all combinations of 20 faces, 19 individuals and a 20-image population average (380 total dyads), using a matching-to-sample task. Multidimensional scaling (MDS) was used to generate a two-dimensional plot representing the feature dimensions of face space. Additionally, human experts provided distinctiveness ratings for each face using a 5-point scale. From the MDS plot, we measured the vector length from each face to the origin, as well as vector angle separating each of the 190 face dyads. As predicted by the face space model, distinctiveness ratings were significantly correlated with vector lengths (p< 0.02): the average face was rated most typical and had one of the shortest vectors. Chimpanzees’ also performed significantly better discriminating distinctive faces compared to typical faces (p< 0.001). Notably, the worst performance was for the average face. Finally, faces separated by the shorter angles, suggesting similar diagnostic features, were discriminated more poorly than faces separated by large angles (p< 0.001). An analysis of these dimensions provides an indication of the features important for individual discrimination.